Assessing the applicability of distributed acoustic sensing in rupture imaging: a case study with the 2022 Michoacán earthquake

SUMMARY We explore the potential of utilizing distributed acoustic sensing (DAS) for back-projection (BP) to image earthquake rupture processes. Synthetic tests indicate that sensor geometry, azimuthal coverage and velocity model are key factors controlling the quality of DAS-based BP images. We show that mitigation strategies and data processing modifications effectively stabilize the BP image in less optimal scenarios, such as asymmetric geometry, narrow azimuthal coverage and poorly constrained velocity structures. We apply our method to the $M_w7.6$ 2022 Michoacán earthquake recorded by a DAS array in Mexico City. We also conduct a BP analysis with teleseismic data for a reference. We identify three subevents from the DAS-based BP image, which exhibit a consistent rupture direction with the teleseismic results despite minor differences caused by uncertainties of BP with DAS data. We analyse the sources of the associated uncertainties and propose a transferable analysis scheme to understand the feasibility of BP with known source–receiver geometries preliminarily. Our findings demonstrate that integrating DAS recordings into BP can help with earthquake rupture process imaging for a broad magnitude range at regional distances. It can enhance seismic hazard assessment, especially in regions with limited conventional seismic coverage.